Energy Science

Computational Energy Sciences research at ORNL encompasses many important aspects of design and development of energy devices and materials. We focus on numerical methods development and implementation, verification and validation of multiscale (atomistic, micro, meso and continuum) and multiphysics (charge and mass transport, chemical and electrochemical kinetics, thermal transport and mechanics) models that are inherent to various energy materials and devices. We primarily work on computational models that utilize desktops, large clusters and also where needed scale to leadership class computing architectures. Another critical and unique effort is to integrate the modeling effort with ongoing experiments at ORNL and other places to have fully validated simulation capabilities. Sensitivity analysis, optimization and uncertainty quantification is playing a more important role in many of these applications as the forward models have more maturity and the modern computational infrastructure allows for multiple ensembles of these engineering simulations that were not earlier feasible. Below are See the project summaries below for highlights related to some of the applications.

Energy Storage

A key component in reducing our nation's dependence on fossil fuels and diversifying our nation's energy sources will be the development of advanced electrical energy storage technologies. Efficient electrical energy storage systems can enable sporadic sources such as wind and solar to deliver more consistent power to the grid, and transitioning to hybrid and eventually all-electric vehicles will have a dramatic effect on both oil consumption and greenhouse gas emissions. However, particularly in the case of vehicles, development of safe, economical electrical energy storage systems with energy and power densities approaching those of gasoline will require significant scientific and engineering breakthroughs. These breakthroughs require an integrated approach, bringing the full breadth of experiment, theory, and simulation to bear on the challenges in order to achieve the understanding that will enable the development of new materials, chemical systems, and manufacturing processes necessary. We are developing computational tools needed to enable the much-needed improvements in battery technology, and also to specifically address safety issues for LIBs. In addition, these tools will be generally applicable to other energy storage devices, including future chemistries such as Li-Air, supercapacitors, hybrid supercapacitor-batteries, etc.

CAEBAT (Contact Sreekanth Pannala or John Turner)

We are developing a flexible, robust, scalable open-architecture based framework that can integrate models of coupled multiphysics phenomena (charge and thermal transport; electrochemical reactions; mechanical stresses) across the porous 3D structure of the electrodes (cathodes and anodes) and the solid or liquid electrolyte system while obtaining inputs from the lower-length processes through closures based on resolved quantities. The environment has a highly-modular design with well-defined interfaces, carefully-designed data structures, and a lightweight Python backplane. The framework services control the various software components through component adapters and the components communicate with the battery state through state adapters. The battery state is the minimal digital description of the battery in space and time such that a simulation can uniquely step through physics components as appropriate to advance in time from each state point to the next. The OAS (Open Architecture framework), along with physics and support components and the adapters create a virtual software environment for battery designers and researchers known as VIBE (Virtual Integrated Battery Environment).

The objective of this project is to develop and make use of predictive simulation for accelerated combustion development, design, calibration, and control through use of high performance computing resources. This makes use of high performance computing resources at ORNL in collaboration with industry stakeholders. To meet new government regulations on fuel economy and emissions, new predictive simulation approaches are necessary to accelerate the design process of engine-systems. ORNL has experimental and modeling expertise in engine and emission controls technologies. This expertise coupled with ORNL world class computing facilities is well suited to address the challenges of design and the optimization of an ever expanding engine parameter space.

The ORNL team has been working with several automobile and engine manufacturers to leverage ORNL expertise and facilities. The current activities (in close collaboration with industry) are as follows:

Cycle-to-Cycle variations in IC engines: Activity makes use of ORNL demonstrated expertise in the area of characterization and control of nonlinear, reactive systems to address stability and control challenges associated with high-efficiency combustion concepts which tend to operate near the "edge of stability". This includes detailed assessments of high-efficiency, low-emissions combustion approaches (with or without high dilution) and an improved understanding of stochastic and deterministic processes which drive the instabilities often associated with these approaches. This activity supports defining an improved path to higher engine and vehicle efficiency in line with DOE objectives.

Gasoline fuel injector optimization: ORNL resources were recognized to have the potential for enabling ground-breaking strides in understanding and optimizing the design of gasoline fuel injector hole patterns and thus improving engine efficiency. This activity addresses HPC for achieving these improvements through the validation and development of high-fidelity, multi-processor computing codes exercised over a wide range of nozzle design variations.

The Consortium for Advanced Simulation of Light Water Reactors (CASL) brings together an exceptionally capable team that will apply existing modeling and simulation (M&S) capabilities and develop advanced capabilities to create a usable environment for predictive simulation of light water reactors (LWRs). The virtual reactor (VR) simulation capability, known as the Virtual Environment for Reactor Applications (VERA), will incorporate science-based models, state-of-the-art numerical methods, modern computational science and engineering practices, and uncertainty quantification (UQ) and validation against data from operating pressurized water reactors (PWRs). It will couple state-of-the-art fuel performance, neutronics, thermal-hydraulics (T-H), and structural models with existing tools for systems and safety analysis and will be designed for implementation on both today's leadership-class computers and the advanced architecture platforms now under development by the U.S. Department of Energy (DOE).

CASL connects fundamental research and technology development through an integrated partnership of government, academia, and industry that extends across the nuclear energy enterprise. The CASL partner institutions possess the interdisciplinary expertise necessary to apply existing M&S capabilities to real-world reactor design issues and to develop new system-focused capabilities that will provide the foundation for advances in nuclear energy technology. CASL's organization and management plan have been designed to promote collaboration and synergy among the partner institutions, taking advantage of the breadth and depth of their expertise and capitalizing on their shared focus on delivering solutions.

CASL T-H

Oak Ridge is working closely with Los Alamos National Laboratory in developing next-generation high-fidelity CFD codes for multiphase flows. This project encompasses models for multiphase flows, discretization, solvers, and scalability to high performance computers to solve the challenging problems in nuclear reactors.